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周冬

(陕西铁路工程职业技术学院 , 渭南   714000)

摘  要: 为合理掌握软土深基坑的大变形肇灾成因 , 并有效实现其预警分级 。基于软土深基坑所处地质条件 、变形成果等信息 , 在开展基坑大变形特征分析及其肇灾成因分析基础上 , 结合沉降变形 、侧位移变形数据开展其预警分级研究 , 且在预警分级过程中 , 提出先对变形数据进行去噪处理 , 以得到真实变形量 , 再以真实变形量为基础 , 通过累计变形判据和变形速率判据联合实现基坑预警等级划分 。结果表明 : 软土基坑大变形肇灾成因主要包括地层肇灾成因 、降水异常肇灾成因 、临边荷载肇灾成因 、支撑作用不理想肇灾成因 , 各因素并非单一作用 , 是共同耦合作用造成了基坑大变形 ; 同时 , 不同监测项目或监测点的预警等级存在一定差异 , 按不利原则 , 综合确定基坑的预警等级为Ⅳ级。

关键词: 软土 ; 深基坑 ; 肇灾成因 ; 去噪处理; 预警分级

中图分类号: TU47      文献标志码: A      文章编号: 1005-8249 (2026) 05-0108-07

DOI:10. 19860/j. cnki. issn1005-8249. 2026. 05. 016

 

ZHOU Dong

(Shaanxi Railway Institute, Weinan 714000, China)

Abstract: To reasonably grasp the causes of large deformation disasters in soft soil deep foundation pits and effectively achieve their warning classification.  Based on the geological conditions and deformation results of soft soil deep foundation pits, and the analysis of the characteristics of large deformation in foundation pits and the causes of disasters, combined with settlement deformation and lateral displacement deformation data, a warning classification study is carried out. In the warning classification process, it is proposed to first denoise the deformation data to obtain the true deformation amount, and then use the true deformation amount as the basis to jointly achieve the classification of foundation pit warning levels through cumulative deformation criteria and deformation rate criteria.  The results show that the causes of large deformation in soft soil foundation pits mainly include geological hazards, abnormal precipitation hazards, edge load hazards, and inadequate support hazards.  Each factor is not a single effect, but a joint coupling effect that causes large deformation in the foundation pit; At the same time, there are certain differences in the warning levels of different monitoring projects or monitoring points. According to the principle of disadvantage, the warning level of the foundation pit is comprehensively determined as level IV.

Key words: soft soil; deep foundation pit; cause of disaster; noise removal; early warning classification

项目来源 : 陕西省自然科学基础研究计划 (2022JQ-570) ; 陕西铁路工程职业技术学院科研基金 (KY2021-62)。

作者简介 : 周  冬 (1982—) , 男, 硕士, 讲师, 研究方向 : 地下工程与桥梁施工。

收稿日期 : 2024-05-08